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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 965 · 40 questions
TalentJR

AI tip (Data → model → prediction): Training data = the examples (500 labelled leaf photos, old emails marked spam). The model = the learned patterns that training builds. A prediction = the model’s answer about something NEW (naming a new leaf, flagging a new email). The order is always data → model → prediction.

NameDateTime takenScore ___ / 40
  1. 1.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  2. 2.True or false: “recorded spoken words” is training data. (a) False (b) True
  3. 3.True or false: “what training builds” is the model. (a) False (b) True
  4. 4.Which of these is the model? (a) tomorrow’s rain guess (b) 500 labelled leaf photos (c) labelled fruit photos (d) the learned patterns
  5. 5.🔁 What is the right order? (a) data, model, prediction (b) model, prediction, data (c) data, prediction, model (d) prediction, data, model
  6. 6.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  7. 7.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  8. 8.True or false: “the trained program” is the model. (a) True (b) False
  9. 9.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to see if it works (d) to make it slower
  10. 10.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  11. 11.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction
  12. 12.⏩ In machine learning, which comes first: past weather records or flagging a new email? (a) past weather records (b) flagging a new email
  13. 13.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  14. 14.Which of these is training data? (a) the learned patterns (b) what training builds (c) 500 labelled leaf photos (d) the trained program
  15. 15.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
  16. 16.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  17. 17.Which of these is training data? (a) the trained program (b) old emails marked spam (c) typing a new spoken word (d) the learned patterns
  18. 18.True or false: “past weather records” is training data. (a) False (b) True
  19. 19.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it prints labels (d) it takes photos
  20. 20.Which of these is a prediction? (a) what training builds (b) past weather records (c) 500 labelled leaf photos (d) flagging a new email
  21. 21.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
  22. 22.Which of these is the model? (a) typing a new spoken word (b) past weather records (c) the trained program (d) labelled fruit photos
  23. 23.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  24. 24.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  25. 25.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  26. 26.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) a label error (d) training data
  27. 27.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  28. 28.Which of these is a prediction? (a) recorded spoken words (b) old emails marked spam (c) typing a new spoken word (d) 500 labelled leaf photos
  29. 29.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  30. 30.⏩ In machine learning, which comes first: recorded spoken words or flagging a new email? (a) recorded spoken words (b) flagging a new email
  31. 31.Which of these is training data? (a) naming a new leaf (b) flagging a new email (c) recorded spoken words (d) naming a new fruit photo
  32. 32.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
  33. 33.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  34. 34.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  35. 35.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  37. 37.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  38. 38.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  39. 39.True or false: “flagging a new email” is a prediction. (a) False (b) True
  40. 40.⏩ In machine learning, which comes first: flagging a new email or labelled fruit photos? (a) flagging a new email (b) labelled fruit photos

Answer key

  1. the learned patterns
  2. True
  3. True
  4. the learned patterns
  5. data, model, prediction
  6. a prediction
  7. 500 labelled leaf photos
  8. True
  9. to see if it works
  10. the model
  11. the model
  12. past weather records
  13. the model
  14. 500 labelled leaf photos
  15. training data
  16. old emails marked spam
  17. old emails marked spam
  18. True
  19. it learns patterns
  20. flagging a new email
  21. a prediction
  22. the trained program
  23. True
  24. what training builds
  25. a prediction
  26. a prediction
  27. False
  28. typing a new spoken word
  29. old emails marked spam
  30. recorded spoken words
  31. recorded spoken words
  32. 500 labelled leaf photos
  33. False
  34. a prediction
  35. False
  36. what training builds
  37. training data
  38. the learned patterns
  39. True
  40. labelled fruit photos

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